Defense Advanced Research Projects AgencyTagged Content List

Imagery and Visualization

Visual representations of data and information

Showing 7 results for Imagery + Analytics RSS
10/11/2017
The rapid pace of new commercial satellite constellation launches has led to a significant increase in the amount and availability of geospatial imagery. Unfortunately, no straightforward way currently exists for analysts to access and analyze all of that imagery. The current ad hoc, time-intensive approach requires gathering and curating data from a large number of available sources, downloading it to specific locations, and running it through separate suites of analytics tools.
August 28, 2019, 8:00 AM EDT,
DARPA Conference Center
The Information Innovation Office is holding a Proposers Day meeting to provide information to potential performers on the new Semantic Forensics (SemaFor) program. SemaFor seeks to develop innovative semantic technologies for automatically analyzing multi-modal media assets (i.e., text, audio, image, video) to defend against large-scale, automated disinformation attacks. Semantic detection algorithms will determine if media is generated or manipulated; attribution algorithms will infer if media originates from a particular organization or individual; characterization algorithms will reason about whether media was generated or manipulated for malicious purposes. The results of detection, attribution, and characterization algorithms will be used to develop explanations for system decisions and prioritize assets for analyst review. SemaFor technologies could help to identify, understand, and deter adversary disinformation campaigns.
The United States Government has an interest in developing and maintaining a strategic understanding of events, situations, and trends around the world, in a variety of domains. The information used in developing this understanding comes from many disparate sources, in a variety of genres, and data types, and as a mixture of structured and unstructured data. Unstructured data can include text or speech in English and a variety of other languages, as well as images, videos, and other sensor information.
The Geospatial Cloud Analytics (GCA) program is developing technology to rapidly access the most up-to-date commercial and open-source satellite imagery, as well as automated machine learning tools to analyze this data. Current approaches to geospatial analysis are ad hoc and time intensive, as they require gathering and curating data from a large number of available sources, downloading the data to specific locations, and running it through separate suites of analytics tools.
The U.S. Government operates globally and frequently encounters so-called “low-resource” languages for which no automated human language technology capability exists. Historically, development of technology for automated exploitation of foreign language materials has required protracted effort and a large data investment. Current methods can require multiple years and tens of millions of dollars per language—mostly to construct translated or transcribed corpora.